Methodology

Background: Community Fact Finder runs demographic summaries for a half mile radius of any point drawn in California. The demographic data is from the Census Bureaus’ American Community 2008-13 5-year survey. To operate, the program draws a half mile circle around the selected point. It then finds all of the block groups that intersect with that radius. The intersected block groups are split so only the portion of the block group polygons that are inside of the polygon are retained. While splitting the block groups, the program assumes and equal distribution of population. Therefore, if only 1/3 of the block group is inside of the radius, only 1/3 of the population is counted. The resulting full and partial block groups are then summarized and reported. While this method produces accurate results in urban areas, rural areas with small pocket populations can be improved. To improve rural area calculations, one needs to distribute the block group data proportionally down to the census block level. This is done to avoid large geographic block groups with a small populated portion from being over distributed. For example, a block group covers 35 square miles with a population of 1,000. Inside that block group there is one contiguous 5 square mile cluster with 900 people, the other 100 people are spread out over the remaining 30 square miles. By breaking the block group geometry down to blocks you can more accurately place the population and reported demographics.

Methods to distribute demographic data to block level:

Data available – American Community Survey 2009-13 5 year estimates at a block group geometry and attributes of interest (population, median household income, and unemployment), 2010 decennial Census block geometry and population

Goal – Distribute the ACS 2009-13 attributes down to the 2010 block geometry.

General outline of methods –

Using the Census 2010 data, for each block, calculate the percent of the block group population it contains.Example:Block group Population 1,000Block 1 = 500 people, it contains 50% of the parent block group populationBlock 2 = 250 people, it contains 25% of the parent block group populationBlock 3 = 250, it contains 25% of the parent block group population

Apply this proportion of each S attribute from the ACS 2009-13 data at the block group level down to the block level.

Using the Census 2010 data, for each block, calculate the percent of the block group household count it contains.Example:Block group Household count 100Block 1 = 50 homes, it contains 50% of the parent block group populationBlock 2 = 25 homes, it contains 25% of the parent block group populationBlock 3 = 25 homes, it contains 25% of the parent block group population

Each time a circle is identified the CFF tool reviews the block groups overlapped by the circle. If any of the block groups are classified as rural, the tool uses the block level allocated estimates forthe attribute reporting. Circles do not mix block group and block input methods – this avoids possible edge matching issues.

American Community Survey (ACS) 2009-2013 5-year estimates, block groups:
Initially 23,212 block groups in California
67 block groups were removed because they had no population: 22 had no land (coastal, water), 45 we reserves, tribal lands, etc.
California population 37,659,181

The method used a mix of data sets, the 2010 decennial census (point-in-time, count) and the 2009-13 5-year American Community Survey (period, estimate).

The ACS data set represents an estimate over a five year period. While it does not represent any one year, it is assumed to most closely resemble the mid-year of the survey; in this case 2011. 1, 2

To improve site performance the urban/rural designation is done at the block group level. This is done by reviewing all block groups within a circle. If any block group in the circle contains a block the census designates as rural, the entire service area is calculated at a block level.

The ACS 2009-13 population and 2010 block (added to block group) population were not compared on a block group to block group level for major differences. Given the use of the decennial and ACS data sets differences will occur between the two data sets because of differences in years and methods. Additionally, the ACS data has estimates that are more recent and may more accurately reflect population distribution, particularly in areas recently developed.

1https://www.nhgis.org/user-resources/faq#compare_ACS_and_decennial, cited 4/29/2015 “Which ACS year range is best for comparisons with decennial censuses? For comparisons with older census data, NHGIS highly recommends using an ACS dataset with a year range centered on 2010 (the 2010 1-year data, the 2009-2011 3-year data, or the 2008-2012 5-year data) in order to maintain a consistent decade interval between the "center points" of the study's measurement periods.”

This site was developed and designed by the California Department of Parks and Recreation Office of Grants and Local Services (OGALS) in collaborationwith GreenInfo Network (www.greeninfo.org), a nonprofit that supports public groups and agencies with geospatial technology.